UseCasesFor.ai

AI Use Cases

A collection of over 250 uses for artificial intelligence

A continually updated list exploring how different types of AI are used across various industries and AI disciplines,including generative AI use cases, banking AI use cases, AI use cases in healthcare, AI use cases in government, AI use cases in insurance, and more

Sign up

to receive a PDF containing all the use cases and stay updated with the latest AI trends and news (you can always unsubscribe)

Insurance premium calculation

Introduction

The insurance industry is considered to be one of the oldest industries in the world, which has the main function of offering protection to people, organizations and even communities. Nevertheless, the determination of insurance premiums, the costs of coverage, has never been an easy calculation. Conventionally, the insurance organizations used historical information, actuarial tables and statistical models to assess the risk profile and work out the premiums. But with the help of the ML and AI, there is a shift in the insurance premium calculation. ML and AI have the potential of dealing with large data sets, identifying trends and making forecasts. This has made the calculation of insurance premiums to be more precise, faster and justifiable thus revolutionizing the insurance industry.

Challenges

There are, however, some challenges that can hinder the application of ML and AI in insurance premium calculations. One of the major barriers is the issue of data: ML algorithms need large amounts of quality data in order to operate properly. However, insurance companies do not have easy access to this type of data because of the issues such as data privacy, legal requirements and limited cooperation between different insurance organisations. Another problem is that applying ML and AI into current processes and structures is a complicated process. This is because it is capital-intensive in terms of time, money, and technical knowledge. There is also a possibility of bias in AI algorithms which may result into unfair premium rates. Also, the black box issue or the challenge of explaining the AI decision-making process is another challenge when it comes to insurance since there are laws that govern the premium calculation models.

AI Solutions

There are challenges that can be solved with the help of ML and AI solutions to help utilize data for insurance premium calculations. For example, sophisticated ML models can help to examine a massive amount of data that can be impossible for a human to analyze and, therefore, make better risk assessments. It also has the potential of simplifying the premium calculation process in the insurance industry by performing routine tasks that would otherwise be done by humans and with minimal errors. Also, AI can also offer explainability of its decisions so as to help overcome the ‘black box’ challenge. Some of the companies that are leveraging AI in the insurance sector include Lemonade and Tractable. Lemonade has also leveraged the use of AI to manage claims and set premiums, while Tractable has employed AI to estimate the extent of damage in insurance claims which in turn facilitates timely and efficient processing of claims as well as cost effectiveness.

Benefits

There are a lot of advantages of using ML and AI in insurance premium calculations as well. The first and probably the most important benefit is that they may provide better risk assessment which means that customers will be charged reasonable premiums. It also can optimize the premium calculation process and eliminate the need for human intervention and thus reduce operational costs and increase efficiency. In addition, through the enhancement of decision-making, AI can help improve the confidence of the insurance industry. Furthermore, the use of AI makes it possible to develop specific insurance products according to the risk appraisal of particular clients, which, in its turn, may contribute to the changes in the insurance market towards the client.

Return on Investment

It can be argued that the return on investment (ROI) of applying ML and AI in insurance premium calculations can be quite high. A research done by McKinsey has revealed that AI can cause the claims costs to drop by 10-15%, the operational costs to drop by 15-25% and the sales conversion to increase by 10-20%. Also, companies such as Lemonade have demonstrated that AI can enhance claim processing by shortening the time it takes to process a claim from weeks to minutes hence cutting on costs. However, the ROI will vary based on some factors such as the quality of data, the complexity of the ML and AI algorithms, and the extent of integration with other systems and business processes.

Choose Topic